def test_empty_list(self): # Set up fragmentation function pg = pegasus_graph(3) fragment_tuple = get_tuple_fragmentation_fn(pg) # Fragment pegasus coordinates fragments = fragment_tuple([]) self.assertEqual([], fragments)
def test_single_vertical_coordinate(self): # Set up fragmentation function pg = pegasus_graph(6) fragment_tuple = get_tuple_fragmentation_fn(pg) pegasus_coord = (0, 1, 3, 1) fragments = fragment_tuple([pegasus_coord]) expected_fragments = {(7, 7, 0, 1), (8, 7, 0, 1), (9, 7, 0, 1), (10, 7, 0, 1), (11, 7, 0, 1), (12, 7, 0, 1)} self.assertEqual(expected_fragments, set(fragments))
def test_single_horizontal_coordinate(self): # Set up fragmentation function pg = pegasus_graph(2) fragment_tuple = get_tuple_fragmentation_fn(pg) # Fragment pegasus coordinates pegasus_coord = (1, 0, 0, 0) fragments = fragment_tuple([pegasus_coord]) expected_fragments = {(0, 3, 1, 0), (0, 4, 1, 0), (0, 5, 1, 0), (0, 6, 1, 0), (0, 7, 1, 0), (0, 8, 1, 0)} self.assertEqual(expected_fragments, set(fragments))
def test_list_of_coordinates(self): # Set up fragmentation function pg = pegasus_graph(6) fragment_tuple = get_tuple_fragmentation_fn(pg) # Fragment pegasus coordinates pegasus_coords = [(1, 5, 11, 4), (0, 2, 2, 3)] fragments = fragment_tuple(pegasus_coords) expected_fragments = {(35, 29, 1, 1), (35, 30, 1, 1), (35, 31, 1, 1), (35, 32, 1, 1), (35, 33, 1, 1), (35, 34, 1, 1), (19, 13, 0, 0), (20, 13, 0, 0), (21, 13, 0, 0), (22, 13, 0, 0), (23, 13, 0, 0), (24, 13, 0, 0)} self.assertEqual(expected_fragments, set(fragments))
def find_clique_embedding(k, m=None, target_graph=None): """Find an embedding of a k-sized clique on a Pegasus graph (target_graph). This clique is found by transforming the Pegasus graph into a K2,2 Chimera graph and then applying a Chimera clique finding algorithm. The results are then converted back in terms of Pegasus coordinates. Note: If target_graph is None, m will be used to generate a m-by-m Pegasus graph. Hence m and target_graph cannot both be None. Args: k (int/iterable/:obj:`networkx.Graph`): Number of members in the requested clique; list of nodes; a complete graph that you want to embed onto the target_graph m (int): Number of tiles in a row of a square Pegasus graph target_graph (:obj:`networkx.Graph`): A Pegasus graph Returns: dict: A dictionary representing target_graphs's clique embedding. Each dictionary key represents a node in said clique. Each corresponding dictionary value is a list of pegasus coordinates that should be chained together to represent said node. """ # Organize parameter values if target_graph is None: if m is None: raise TypeError("m and target_graph cannot both be None.") target_graph = pegasus_graph(m) m = target_graph.graph['rows'] # We only support square Pegasus graphs _, nodes = k # Deal with differences in ints vs coordinate target_graphs if target_graph.graph['labels'] == 'nice': fwd_converter = get_nice_to_pegasus_fn(m=m) back_converter = get_pegasus_to_nice_fn(m=m) pegasus_coords = [fwd_converter(*p) for p in target_graph.nodes] back_translate = lambda embedding: { key: [back_converter(*p) for p in chain] for key, chain in embedding.items() } elif target_graph.graph['labels'] == 'int': # Convert nodes in terms of Pegasus coordinates coord_converter = pegasus_coordinates(m) pegasus_coords = map(coord_converter.tuple, target_graph.nodes) # A function to convert our final coordinate embedding to an ints embedding back_translate = lambda embedding: { key: list(coord_converter.ints(chain)) for key, chain in embedding.items() } else: pegasus_coords = target_graph.nodes back_translate = lambda embedding: embedding # Break each Pegasus qubits into six Chimera fragments # Note: By breaking the graph in this way, you end up with a K2,2 Chimera graph fragment_tuple = get_tuple_fragmentation_fn(target_graph) fragments = fragment_tuple(pegasus_coords) # Create a K2,2 Chimera graph # Note: 6 * m because Pegasus qubits split into six pieces, so the number of rows and columns # get multiplied by six chim_m = 6 * m chim_graph = chimera_graph(chim_m, t=2, coordinates=True) # Determine valid fragment couplers in a K2,2 Chimera graph edges = chim_graph.subgraph(fragments).edges() # Find clique embedding in K2,2 Chimera graph embedding_processor = processor(edges, M=chim_m, N=chim_m, L=2, linear=False) chimera_clique_embedding = embedding_processor.tightestNativeClique( len(nodes)) # Convert chimera fragment embedding in terms of Pegasus coordinates defragment_tuple = get_tuple_defragmentation_fn(target_graph) pegasus_clique_embedding = map(defragment_tuple, chimera_clique_embedding) pegasus_clique_embedding = dict(zip(nodes, pegasus_clique_embedding)) pegasus_clique_embedding = back_translate(pegasus_clique_embedding) if len(pegasus_clique_embedding) != len(nodes): raise ValueError("No clique embedding found") return pegasus_clique_embedding
def find_clique_embedding(k, m=None, target_graph=None): """Find an embedding for a clique in a Pegasus graph. Given a clique (fully connected graph) and target Pegasus graph, attempts to find an embedding by transforming the Pegasus graph into a :math:`K_{2,2}` Chimera graph and then applying a Chimera clique-finding algorithm. Results are converted back to Pegasus coordinates. Args: k (int/iterable/:obj:`networkx.Graph`): A complete graph to embed, formatted as a number of nodes, node labels, or a NetworkX graph. m (int): Number of tiles in a row of a square Pegasus graph. Required to generate an m-by-m Pegasus graph when `target_graph` is None. target_graph (:obj:`networkx.Graph`): A Pegasus graph. Required when `m` is None. Returns: dict: An embedding as a dict, where keys represent the clique's nodes and values, formatted as lists, represent chains of pegasus coordinates. Examples: This example finds an embedding for a :math:`K_3` complete graph in a 2-by-2 Pegaus graph. >>> from dwave.embedding.pegasus import find_clique_embedding ... >>> print(find_clique_embedding(3, 2)) # doctest: +SKIP {0: [10, 34], 1: [35, 11], 2: [32, 12]} """ # Organize parameter values if target_graph is None: if m is None: raise TypeError("m and target_graph cannot both be None.") target_graph = pegasus_graph(m) m = target_graph.graph['rows'] # We only support square Pegasus graphs _, nodes = k # Deal with differences in ints vs coordinate target_graphs if target_graph.graph['labels'] == 'nice': fwd_converter = get_nice_to_pegasus_fn() back_converter = get_pegasus_to_nice_fn() pegasus_coords = [fwd_converter(*p) for p in target_graph.nodes] back_translate = lambda embedding: {key: [back_converter(*p) for p in chain] for key, chain in embedding.items()} elif target_graph.graph['labels'] == 'int': # Convert nodes in terms of Pegasus coordinates coord_converter = pegasus_coordinates(m) pegasus_coords = map(coord_converter.tuple, target_graph.nodes) # A function to convert our final coordinate embedding to an ints embedding back_translate = lambda embedding: {key: list(coord_converter.ints(chain)) for key, chain in embedding.items()} else: pegasus_coords = target_graph.nodes back_translate = lambda embedding: embedding # Break each Pegasus qubits into six Chimera fragments # Note: By breaking the graph in this way, you end up with a K2,2 Chimera graph fragment_tuple = get_tuple_fragmentation_fn(target_graph) fragments = fragment_tuple(pegasus_coords) # Create a K2,2 Chimera graph # Note: 6 * m because Pegasus qubits split into six pieces, so the number of rows and columns # get multiplied by six chim_m = 6 * m chim_graph = chimera_graph(chim_m, t=2, coordinates=True) # Determine valid fragment couplers in a K2,2 Chimera graph edges = chim_graph.subgraph(fragments).edges() # Find clique embedding in K2,2 Chimera graph embedding_processor = processor(edges, M=chim_m, N=chim_m, L=2, linear=False) chimera_clique_embedding = embedding_processor.tightestNativeClique(len(nodes)) # Convert chimera fragment embedding in terms of Pegasus coordinates defragment_tuple = get_tuple_defragmentation_fn(target_graph) pegasus_clique_embedding = map(defragment_tuple, chimera_clique_embedding) pegasus_clique_embedding = dict(zip(nodes, pegasus_clique_embedding)) pegasus_clique_embedding = back_translate(pegasus_clique_embedding) if len(pegasus_clique_embedding) != len(nodes): raise ValueError("No clique embedding found") return pegasus_clique_embedding